International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Open Access | Double Blind Reviewed

ISSN: 2319-7064


Downloads: 103

Research Paper | Mathematics | Kenya | Volume 3 Issue 6, June 2014


Comparative Study of Performance of Neural Networks with Other Non-Parametric Regression Estimators

Robert Kasisi [2]


Abstract: Neural Neural networks have drawn attention to researchers in recent years. This is because they show superiority as a modeling technique for datasets showing nonlinear relationships and thus for both data fitting and prediction abilities. In this study we derive a neural network estimator of finite population mean. This study shows that the mean square error values of the neural network estimator are minimal compared to those of other nonparametric estimators. This implies that neural networks are a better estimation technique for estimating population mean.


Keywords: Neural networks, nonlinear model, nonparametric regression, auxiliary information, survey sampling


Edition: Volume 3 Issue 6, June 2014,


Pages: 1291 - 1294


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How to Cite this Article?

Robert Kasisi, "Comparative Study of Performance of Neural Networks with Other Non-Parametric Regression Estimators", International Journal of Science and Research (IJSR), Volume 3 Issue 6, June 2014, pp. 1291-1294, https://www.ijsr.net/get_abstract.php?paper_id=20131418

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